• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.2
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• pp.65-70
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• 2009

In this paper, we introduced the notion of (L,$\bigodot$)-quasi-uniform spaces and (L,$\bigodot$)-neighborhood systems on a strictly two-sided, commutative quantale lattice L. We investigate their properties and give the examples. In particular, we study the relations between (L,$\bigodot$)-quasi-uniform spaces and (L,$\bigodot$)-neighborhood systems.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.1-12
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• 2020

This study aimed to select and evaluate policy priorities for the expansion of public and semi-public systems for coastwise passenger transport services. For research methodology, the Consistent Fuzzy Preference Relations (CFPR) method was used to effectively extract expert knowledge. First, the result of the analysis on policy tasks for expanding the semi-public system for coastwise passenger transport services showed that "the establishment of public transportation fare system" was the most important task at 0.160. Second, "conversion of the subsidiary routes to a public system by the central government" was ranked next at the importance of 0.136. The factor named "support through proper allocation of budgets between national and local governments" are ranked third (0.119). The results of this study have practical implications in that it proposed the policy priorities for the expansion of the public semi-public systems for coastwise passenger transport services.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.59-71
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• 2019

This research is aimed to identify the building factors and deriving the importance of each factor for establishing the smart distribution center in the fourth industrial revolution era. The research methodology used CFPR(Consistent Fuzzy Preference Relations) to effectively extract expert knowledge. Research has shown as principle factors that "Service" is the first factor to be considered as 0.271, followed by "Infra(Warehouse)"(0.254), "Information System"(0.247), and "Equipment"(0.228). And as detailed factors, "Reliability" showed the highest importance as 0.091, followed "Visibility of Information System"(0.076), "Space Advancement"(0.075), "Location"(0.074) and "Satisfaction of service"(0.073). This study has implications in that it has presented an establishment direction for the smart distribution center.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.525-531
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• 2020

In today's IT environment where various pieces of information are distributed in large volumes, recommendation systems are in the spotlight capable of figuring out users' needs fast and helping them with their decisions. The current recommendation systems, however, have a couple of problems including that user preference may not be reflected on the systems right away according to their changing tastes or interests and that items with no relations to users' preference may be recommended, being induced by advertising. In an effort to solve these problems, this study set out to propose a Fuzzy-AHP-based movie recommendation system by applying the BRNN(Bidirectional Recurrent Neural Network) language model. Applied to this system was Fuzzy-AHP to reflect users' tastes or interests in clear and objective ways. In addition, the BRNN language model was adopted to analyze movie-related data collected in real time and predict movies preferred by users. The system was assessed for its performance with grid searches to examine the fitness of the learning model for the entire size of word sets. The results show that the learning model of the system recorded a mean cross-validation index of 97.9% according to the entire size of word sets, thus proving its fitness. The model recorded a RMSE of 0.66 and 0.805 against the movie ratings on Naver and LSTM model language model, respectively, demonstrating the system's superior performance in predicting movie ratings.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.129-141
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• 2001

Kansei engineering or image technology is a tool to analyze relation between product design components and the impression or feeling of human for physical products. This paper attempts to construct the designer\`s aid tool for developing corporate identity(CI) symbol mark based on the hybrid Kansei engineering. It combines the forward Kansei engineering for translating consumer\`s feeling into design components of CI symbol mark and the backward Kansei engineering for evaluating consumer\`s feeling for CI symbol mark. The semantic differential(SD) evaluation experiment is carried out to find the relations between image and design. The backward Kansei engineering system is modelled by fuzzy neural network. This research is expected to contribute to the development of CI symbol mark that correspond to comsumer\`s image.

• Korea Trade Review
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• v.44 no.1
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• pp.193-205
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• 2019

It is important to accurately analyze the various factors such as the local situation of the purchasable countries and the international situation in order to export defense industrial goods developed in Korea and to enter overseas markets based on the results. In the case of defense materials, unlike the civilian sector, there are a limited number of countries with high export potential. Therefore, to select a possible export market, it is necessary to consider the purchasing power index through the examination of the purchasability of the exportable market. Therefore, the present study chose a total of 18 purchasing power indicators in five major categories of economic power, military power, defense science and technology level, friendly relations with Korea, and possibility of dispute. By calculating each weight with AHP and Fuzzy-AHP analysis, the results was presented the purchasing power index and the weighting. Based on the results will contribute to the study on the method of selecting the export market of the defense materials and the establishment of the export policy of the defense industry.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.304-309
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• 2013

This paper proposes a intelligent approach on range decision of figure of merit. Unknown range of the underwater target and the non-fixed signal excess make the uncertainty for the tracking process. Using the input data of signal excess related to the range, we establish the rule of the fuzzy set and the original data acquired by sonar can be transformed to the fuzzified data set. To reduce the error arisen from the unexpected data, we use the new data transformed in fuzzy set. The piecewise relations of the min value, max one, and the mean one are calculated. The three values are used for the expected range of the underwater target. By analysing the fluctuation of the data, we can expect the target's position and the characteristics of the maneuvering. The examples are presented to show the performance and the effectiveness of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.49-53
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• 2011

Path following of the mobile robot is one research hot for the mobile robot navigation. For the control system of the wheeled mobile robot(WMR) being in nonhonolomic system and the complex relations among the control parameters, it is difficult to solve the problem based on traditional mathematics model. In this paper, we presents a simple and effective way of implementing an adaptive following controller based on the PID for mobile robot path following. The method uses a non-linear model of mobile robot kinematics and thus allows an accurate prediction of the future trajectories. The proposed controller has a parallel structure that consists of PID controller with a fixed gain. The control law is constructed on the basis of Lyapunov stability theory. Computer simulation for a differentially driven nonholonomic mobile robot is carried out in the velocity and orientation tracking control of the nonholonomic WMR. The simulation results of wheel type mobile robot platform are given to show the effectiveness of the proposed algorithm.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2001.11a
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• pp.139-144
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• 2001

Insulation aging diagnosis system provides early warning regarding electrical equipment defect. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. Since relations of insulation aging and partial discharge dynamics are non-linear, it is very difficult to provide early warning in an electrical equipment. In this paper, we propose the design method of insulation aging diagnosis system that use a magnetic wave and acoustic signal to diagnoses an electrical equipment. Proposed system measures the partial discharge on-line from DAS(Data Acquisition System) and acquires 2D patterns from analyzing it. For filtering the noise contained in sensor signals we used ICA algorithms. Using this data, design of the neuro-fuzzy model that diagnoses an electrical equipment is investigated. Validity of the new method is asserted by numerical simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.446-451
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• 1992

In this paper, we propose a method to manage production system easily for operators when either equipments or products are changed. And we explain the scheduling AI tool which realizes the proposal method. The tool's knowledge expression consists of models, rules, mathematical expression and fuzzy logic. The model expresses the relations between products and manufacture, and properties of products. The models are separated into three type, equipment model, operation model, and product model. These models are classified by applicable fields as the assembly process or continuous plant process, The model expression of each type is based on object oriented paradigm. We report systems utilizing our approach.